Hacer más exámenes es fácil. Gestionarlos es cada vez más difícil.

Test automation keeps growing. Teams are building more Appium tests, expanding their coverage, and AI is only accelerating that growth.

But when it’s time for regression testing, the same tests that are supposed to give you confidence can fail for reasons that aren’t immediately obvious. Was it an actual defect? A temporary connectivity issue? Or a test that’s been unreliable for weeks?

Someone has to figure that out, and the more tests you have, the more time that can take.

The challenge isn’t just running more tests. It’s managing how those tests run, knowing which failures need attention, and getting the right feedback at the right time.

The problem isn’t always the test

Consider a regression suite with hundreds of tests running across different devices.

A few tests fail. An engineer reruns them to see whether the failures repeat. Some pass on the second attempt, others continue failing. Meanwhile, a critical test may have failed early in the run, but the team doesn’t find out until the execution finishes.

None of this is particularly unusual. It’s how many teams manage their automation today.

Frameworks like JUnit and TestNG already support retries, but retries alone don’t address everything around test execution. They don’t necessarily tell you which failures should take priority or make it easy to spot tests that consistently need another attempt to pass.

And as automation suites grow, this becomes harder to manage.

¿Por qué esto se vuelve más caro a medida que crecen las suites? 

Se estima que entre el 40 y el 50 % del código empresarial ahora es generado por IA (Digital.aiMás código significa más posibilidades de fallos, y los conjuntos de pruebas crecen a la par. 

Las pruebas inestables son un problema conocido a gran escala: Atlassian atribuye aproximadamente el 15% de los fallos de su repositorio backend de Jira a pruebas inestables, y las repeticiones resultantes desperdician más de 150,000 horas de desarrollo al año (Atlassian, 2025). 

Si aún estás ajustando localizadores y esperas, comienza con Reintentar la operación no solucionará un problema de localización.. But even with reliable tests, teams still need a better way to manage execution, understand failures, and get feedback when it matters.

Orquestador de pruebas: una capa intermedia para la ejecución de las pruebas 

Digital.ai Testing now includes Test Orchestrator, a middle layer between your existing Appium tests and the Digital.ai Testing platform. Rather than changing how your tests are written, Test Orchestrator focuses on what happens when those tests run.

There are three things worth highlighting:

• Reintentos automáticos: Failed tests are retried automatically, helping distinguish intermittent failures from repeatable defects. Each attempt and its outcome remain visible.
• Faster feedback on critical tests: Teams can identify critical tests and get feedback sooner when they fail, rather than waiting for the entire run to finish.
• Identifying unreliable tests: Tests that repeatedly fail before passing become easier to spot, giving engineers a clearer starting point for investigating unreliable automation.

The goal isn’t to eliminate every failed test. It’s to reduce the manual effort involved in understanding what happened and deciding what needs attention.

Your tests stay as they are 

One of the important things about Test Orchestrator is that you don’t need to rewrite your existing Appium tests.

It’s a Java-based agent distributed as a JAR file. You add it to your existing project, along with a centralized YAML configuration file that defines how tests execute.

Device selection, application configuration, test selection, and retry behavior can all be managed from that configuration file rather than scattered across your project. Combined with MCP, Test Orchestrator also extend AI-driven testing workflows with smarter execution management.

As AI makes it easier to create more tests, managing their execution becomes just as important.

Getting more out of your test automation 

More tests should mean better coverage, not more time spent figuring out why the last regression run failed.

Test Orchestrator helps teams manage that growing complexity through automatic retries, faster feedback on critical tests, and visibility into unreliable automation. And it does so without changing the tests they’ve already built.

Consulte las GitHub project example Para empezar.